New Survey Shows Urgent Need for Data Governance Technology

Information Difference just published a new study based on a survey exploring the links between data governance, master data management (MDM) and data quality. While it’s full of insights, I’m particularly struck by how urgently companies are expressing the need for data governance technology. Read more

Data Governance is a Prerequisite for Effective MDM and Data Quality

Dave Waddington is senior vice president and co-founder of The Information Difference, an analyst firm specializing in data quality, master data management (MDM) and data governance. He is a recognized authority and practitioner in the field of data management and has advised both vendors and corporations on data management strategy and architecture. Read more

How to Measure Data Accuracy?

If you believe that better data quality has huge business value, and you believe the old axiom that you cannot improve something if you cannot measure it, then it follows that measuring data quality is very, very important. And it’s not a one-time exercise. Data quality should be measured regularly to establish a baseline and trend; otherwise continuous improvement wouldn’t be possible. Read more

Is Data Governance 20% Technology?

Last year, I met with the data governance lead of a London-based consulting company. We had a rich and wide-ranging discussion. With considerable violence, we agreed on the need for data governance, and the best way to do it. But when I brought up Kalido software, he clammed up and said, “Data governance is about people and process. Not about technology.” Read more

A Simple Data Governance Framework

It’s not surprising that to new comers, data governance seems very fuzzy and unwieldy. Terms like rules, policies, procedures, standards, process, data quality, security, decision rights, and accountability have been used commonly to describe various aspects of data governance. At first blush, they appear to be a collection of disconnected concepts. Read more

Building a Business Case for Data Governance

In a conversation with a respected analyst last week, we concurred that as a business practice, data governance has just crossed the chasm and entered early mainstream adoption. Like exercising, flossing and recycling, most organizations have come to believe that data governance is a good thing. But it doesn’t mean every organization will do it. Read more

How to Set the Right Initial Scope for Data Governance

Data governance can seem like a daunting task. Described generically, it has the potential to take on an impossibly large scope and a pervasive, enterprise-wide reach. But data governance doesn’t need to solve world hunger … at least not at first. Successful organizations embarking on the data governance journey have thrived by first starting small, proving the value of data governance, and capitalizing on those achievements to expand the scope. The question for those just starting out is: How do we set a manageable initial scope that can produce immediate business benefit while instituting a permanent organizational structure and processes? Read more

What’s the Root Cause of Bad Data?

Starting this week, I’ll be publishing a series of blogs on enterprise data governance. As always, I welcome your comments and feedback.

When it comes to data management, presentations and whitepapers all have a very consistent theme: Data is important, and we need to do something about it. The vendor landscape changed. Technology fashion changed. But the message remains the same, almost as if nobody is aware of the problem or has done anything about it. Read more

Data Governance is the Missing Link between Data and Business Process

In my career, which has spanned both sides of buying and selling IT, one thing hasn’t changed: Data people and business process people don’t talk to each other. Business process people assume that data simply exists and care little about how it is “managed”, while data people focus more on the bits and bytes stored in repositories than how the bits and bytes are created and consumed. With data and process sitting on different layers on enterprise architecture diagrams, the prevailing view is that everything will work as long as the interfaces are well defined. Read more